This is ttv1 code (Timm tools, version 1).
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In use, values are just thrown at a thing
and, internally, this code works
out if we are talking about num
s or sym
s.
thing
s have a variable thing.my
s containing either a num
or a sym
.Apart from sumamries, thing
s also keep a random sample
of the values seen
so far.
thing.samples
.Can be used incrementally, or in batch.
t=thing()
for i in range(1000):#
t + i
if i % 100 == 0: print(t,t.samples.stats())
# output:
{:txt 0 :pos 0 :n 1} (0, 0)
{:txt 0 :pos 0 :n 101} (50, 50)
{:txt 0 :pos 0 :n 201} (100, 100)
{:txt 0 :pos 0 :n 301} (149.5, 154)
{:txt 0 :pos 0 :n 401} (197.5, 205)
{:txt 0 :pos 0 :n 501} (251.5, 249)
{:txt 0 :pos 0 :n 601} (311.0, 287)
{:txt 0 :pos 0 :n 701} (353.5, 362)
{:txt 0 :pos 0 :n 801} (413.5, 415)
{:txt 0 :pos 0 :n 901} (462.5, 450)
{:txt 0 :pos 0 :n 901} (480.5, 443)
t= thing(i for i in range(901))
print(t,t.samples.stats())
# output
{:txt 0 :pos 0 :n 69}
from num import num
from sym import sym
from sample import sample
class thing:
UNKNOWN = "?"
Initialization
def __init__(i,inits=[],pos=None, txt=None,samples=None):
pos = pos or 0
txt = txt or pos
i.txt=str(txt)
i.pos=pos
i.my=None # will contain a `num` or a `sym`, depending on what data arrives
i.samples=None
[i + x for x in inits]
Pretty print
def __repr__(i):
return '%s{:txt %s :pos %s :n %s}' % (
(i.my.__class__.__name__ if i.my else ""),
i.txt,i.pos,i.n())
Updating. If this our first item, then work out the type
and initialize the internal summary variable.
Also, ensure we have a pace to store the random samples
.
def __add__(i,xs):
for x in i.items(xs):
if i.my is None:
what = num if isinstance(x,(float,int)) else sym
i.my = what()
if i.samples is None:
i.samples = sample()
i.my + x
i.samples + x
return xs
Iterating over items. If passed a list then yield each item.
Otherwise, just yield the passed in argument.
But do not yield anything that is an UNKNOWN
value.
def items(i,xs):
xs = xs if isinstance(xs,(list,tuple)) else [xs]
for x in xs:
if x != thing.UNKNOWN:
yield x
Much of thing
's services are defined in terms of the nested
internal summary variables.
For example, here's how we compute
the number of items seen by this thing
.
def n(i):
return i.my.n
def dist(i,j,k) : return i.my.dist(j,k)
def cliffsDelta(i,j): return i.samples.cliffsDelta(j.samples)
def ranges(i) : return i.samples.ranges()
def bootstrap(i,j) : return i.samples.bootstrap(j.samples)
def same_CD(i,j) : return i.cliffsDelta(j) and i.bootstrap(j)
Parametric. assumes gaussians
def same_HT(i,j) : return i.hedges(j) and i.ttest(j)
def ttest(i,j) : return i.my.ttest(j.my)
Copyright © 2016,2017 Tim Menzies tim@menzies.us, MIT license v2.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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